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| Registros recuperados : 34 | |
| 21. |  | MISZTAL, I.; FRAGOMENI, B.; LOURENÇO, D. A. L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; LAWLOR, T. J. Efficient inversion of genomic relationship matrix by the Algorithm for Proven and Young (APY). Interbull Bulletin, 2015, v. 49, p. 111-116.| Biblioteca(s): INIA Las Brujas. |
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| 22. | | FRAGOMENI, B.O.; LOURENCO, D.A.L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; LAWLOR, T.J.; MIZTAL, I. Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes. Journal of Dairy Science, 2015, v.98, no.6, p.4090-4094. OPEN ACCESS. Article history: Received November 18, 2014 / Accepted March 13, 2015 / Published online: April 8, 2015.| Biblioteca(s): INIA Las Brujas. |
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| 23. | | MASUDA, Y.; MISZTAL, I.; TSURUTA, S.; LEGARRA, A.; AGUILAR, I.; LOURENCO, D.A.L.; FRAGOMENI, B.O.; LAWLOR, T.J. Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals. Journal of Dairy Science, 2016, v.99, no.3, p.1968-1974. OPEN ACCESS OPEN ACCESS. Received 19 October 2015, Accepted 1 December 2015, Available online 21 January 2016| Biblioteca(s): INIA Las Brujas. |
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| 24. | | MCWHORTER, T.M.; BERMANN, M.; GARCIA, A.L.S.; LEGARRA, A.; AGUILAR, I.; MISZTAL, I.; LOURENCO, D. Implication of the order of blending and tuning when computing the genomic relationship matrix in single-step GBLUP. Journal of Animal Breeding and Genetics, 2023, volume 140, issue 1, pp. 60-78. OPEN ACCESS. doi: https://doi.org/10.1111/jbg.12734 Article history: Received 18 March 2019; Revised 15 July 2019; Accepted: 29 July 2019; First published 10 August 2022.
Correspondence: McWhorter, T.M.; Department of Animal and Dairy Science, University of Georgia, Athens, GA, United...| Biblioteca(s): INIA Las Brujas. |
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| 25. | | LOURENCO, D.A.L.; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; EZRA, E.; RON, M.; SHIRAK, A.; WELLER, J.I. Methods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses. Journal of Dairy Science, 2014, v.97, no.3, p.1742-1752. OPEN ACCESS. Article history: Received September 10, 2013. / Accepted December 6, 2013.| Biblioteca(s): INIA Las Brujas. |
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| 26. | | LONDOÑO-GIL, M.; LÓPEZ-CORREA, R.; AGUILAR, I.; MAGNABOSCO, C.U.; HIDALGO, J.; BUSSIMAN, F.; BALDI, F.; LOURENCO, D. Strategies for genomic predictions of an indicine multi-breed population using single-step GBLUP. Journal of Animal Breeding and Genetics, 2024. https://doi.org/10.1111/jbg.12882 - [Early view] Article history: Received 22 March 2024, Revised 10 May 2024, Accepted 15 May 2024. -- Corresponding author: Londoño-Gil, M.; Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Via de...| Biblioteca(s): INIA Las Brujas. |
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| 27. | | LOURENCO, D.; TSURUTA, S.; FRAGOMENI, B.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; MILLER, S.; MOSER, D.; MISZTAL, I. Single-step genomic BLUP for national beef cattle evaluation in US: from initial developments to final implementation. Volume Species - Bovine (beef) 1, 495. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018.| Biblioteca(s): INIA Las Brujas. |
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| 28. | | MASUDA, Y.; MISZTAL, I.; TSURUTA, S.; LOURENÇO, D. A. L.; FRAGOMENI, B.; LEGARRA, A.; AGUILAR, I.; LAWLOR, T. J. Single-step genomic evaluations with 570K genotyped animals in US Holsteins. Interbull Bulletin, 2015, v. 49, p. 85-89.| Biblioteca(s): INIA Las Brujas. |
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| 29. | | MASUDA, Y; MISZTAL, I.; LEGARRA, A.; TSURUTA, S.; LOURENCO, D.A.L.; FRAGOMENI, B.O.; AGUILAR, I. Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient. Journal of Animal Science, 2017, v. 95(1): 49-52. Article history: Received: July 05, 2016; Accepted: Aug 16, 2016; Published: February 2, 2017.
This research was partially funded by the United States Department of Agriculture?s National Institute of Food and Agriculture (Agriculture and...| Biblioteca(s): INIA Las Brujas. |
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| 30. | | LOURENCO, D. A. L.; TSURUTA, S.; FRAGOMENI, B. O.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; BERTRAND, J. K.; AMEN, T. S.; WANG. L.; MOSER, D. W.; MISZTAL, I. Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus.(*) Journal of Animal Science, 2015, v. 93, p. 2653-2662. Published June 25, 2015. OPEN ACCESS. (*) This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI), and Agriculture and Food Research Initiative Competitive Grants no. 2015-67015-22936 from the U.S. Department of Agriculture?s...| Biblioteca(s): INIA Las Brujas. |
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| 31. | | LOURENCO, D.A.L.; FRAGOMENI, B.O.; BRADFORD, H.L.; MENEZES I.R.; FERRAZ, J.B.S.; AGUILAR, I.; MISZTAL, I. Implications of SNP weighting on single-step genomic predictions for different reference population sizes. Journal of Animal Breeding and Genetics, 2017, v. 134 (6), p. 463-471. Article history: Received: 28 February 2017 / Accepted: 19 July 2017.
This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI) and by Agriculture and Food Research Initiative Competitive...| Biblioteca(s): INIA Las Brujas. |
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| 32. | | TONUSSI, R.L.; LONDOÑO-GIL, M.; DE OLIVEIRA SILVA, R.M.; MAGALHÃES, A.F.B.; AMORIM, S:T.; KLUSKA, S.; ESPIGOLAN, R.; PERIPOLLI, E.; PEREIRA, A.S.C.; LÔBO, R.B.; AGUILAR, I.; LOURENÇO, D.A.L.; BALDI, F. Accuracy of genomic breeding values and predictive ability for postweaning liveweight and age at first calving in a Nellore cattle population with missing sire information. Tropical Animal Health and Production, 2021, Volume 53, Issue 4, Article number 432. doi: https://doi.org/10.1007/s11250-021-02879-w Article history: Received 19 March 2021; Accepted 30 July 2021; Published online 10 August 2021.
Corresponding author: Londoño-Gil, M.; Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual...| Biblioteca(s): INIA Las Brujas. |
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| 33. | | MISZTAL, I.; WANG, H.; AGUILAR, I.; LEGARRA, A.; TSURUTA, S.; LOURENCO, D.; FRAGOMENI, B. O.; ZHANG, X.; MUIR, W. M.; CHENG, H. H.; OKIMOTO, R.; WING, T.; HAWKEN, R. R.; ZUMBACH, B.; FERNANDO, R. GWAS using ssGBLUP. Volume Species Breeding: Poultry, 325. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.325.| Biblioteca(s): INIA Las Brujas. |
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| 34. | | TONUSSI, R. L.; SILVA, R. M. D. O.; MAGALHÃES, A.F.B.; ESPIGOLAN, R.; PERIPOLLI, E.; OLIVIERI, B. F.; FEITOSA, F. L. B.; LEMOS, M. V. A.; BERTON, M. P.; CHIAIA, H. L. J.; PEREIRA, A. S. C.; LÔBO, R. B.; BEZERRA, L. A. F.; MAGNABOSCO, C. D. U.; LOURENÇO, D.A.L.; AGUILAR, I.; BALDI, F. Application of single step genomic BLUP under different uncertain paternity scenarios using simulated data. (Research article). PLoS ONE, September 2017, Volume 12, Issue 9, Article number e0181752. OPEN ACCESS. Article history: Received September 22, 2016 // Accepted July 6, 2017 // Published September 28, 2017.
Data Availability Statement: All relevant data are within the paper, its Supporting Information files, and in Figshare.
Funding: This...| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 34 | |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
16/08/2022 |
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Actualizado : |
27/04/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
MCWHORTER, T.M.; BERMANN, M.; GARCIA, A.L.S.; LEGARRA, A.; AGUILAR, I.; MISZTAL, I.; LOURENCO, D. |
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Afiliación : |
TAYLOR M. MCWHORTER, Department of Animal and Dairy Science, University of Georgia, Athens, Georgia, USA; MATIAS BERMANN, Department of Animal and Dairy Science, University of Georgia, Athens, Georgia, USA; ANDRE L. S. GARCIA, Department of Animal and Dairy Science, University of Georgia, Athens, Georgia, USA; ANDRÉS LEGARRA, UMR GenPhySE, Institut National de la Recherche Agronomique, Castanet- Tolosan, France; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACY MISZTAL, Department of Animal and Dairy Science, University of Georgia, Athens, Georgia, USA; DANIELA LOURENCO, Department of Animal and Dairy Science, University of Georgia, Athens, Georgia, USA. |
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Título : |
Implication of the order of blending and tuning when computing the genomic relationship matrix in single-step GBLUP. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Journal of Animal Breeding and Genetics, 2023, volume 140, issue 1, pp. 60-78. OPEN ACCESS. doi: https://doi.org/10.1111/jbg.12734 |
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ISSN : |
0931-2668; eISSN: 1439-0388 |
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DOI : |
10.1111/jbg.12734 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 18 March 2019; Revised 15 July 2019; Accepted: 29 July 2019; First published 10 August 2022.
Correspondence: McWhorter, T.M.; Department of Animal and Dairy Science, University of Georgia, Athens, GA, United States; email:taylor.mcwhorter@uga.edu --
This study was partially funded by Agriculture and Food Research Initiative Competitive Grant no. 2020?67015?31030 from the U.S. Department of Agriculture, Australian Government's National Institute of Food and Agriculture (Washington, DC). -- This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. License Creative Commons: https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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Contenido : |
ABSTRACT.- Single-step genomic BLUP (ssGBLUP) relies on the combination of the genomic ((Formula presented.)) and pedigree relationship matrices for all ((Formula presented.)) and genotyped ((Formula presented.)) animals. The procedure ensures (Formula presented.) and (Formula presented.) are compatible so that both matrices refer to the same genetic base (?tuning?). Then (Formula presented.) is combined with a proportion of (Formula presented.) (?blending?) to avoid singularity problems and to account for the polygenic component not accounted for by markers. This computational procedure has been implemented in the reverse order (blending before tuning) following the sequential research developments. However, blending before tuning may result in less optimal tuning because the blended matrix already contains a proportion of (Formula presented.). In this study, the impact of ?tuning before blending? was compared with ?blending before tuning? on genomic estimated breeding values (GEBV), single nucleotide polymorphism (SNP) effects and indirect predictions (IP) from ssGBLUP using American Angus Association and Holstein Association USA, Inc. data. Two slightly different tuning methods were used; one that adjusts the mean diagonals and off-diagonals of (Formula presented.) to be similar to those in (Formula presented.) and another one that adjusts based on the average difference between all elements of (Formula presented.) and (Formula presented.). Over 6 million Angus growth records and 5.9 million Holstein udder depth records were available. Genomic information was available on 51,478 Angus and 105,116 Holstein animals. Average realized relationship estimates among groups of animals were similar across scenarios. Scatterplots show that GEBV, SNP effects and IP did not noticeably change for all animals in the evaluation regardless of the order of computations and when using blending parameter of 0.05. Formulas were derived to determine the blending parameter that maximizes changes in the genomic relationship matrix and GEBV when changing the order of blending and tuning. Algebraically, the change is maximized when the blending parameter is equal to 0.5. Overall, tuning (Formula presented.) before blending, regardless of blending parameter used, had a negligible impact on genomic predictions and SNP effects in this study. © 2022 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd. MenosABSTRACT.- Single-step genomic BLUP (ssGBLUP) relies on the combination of the genomic ((Formula presented.)) and pedigree relationship matrices for all ((Formula presented.)) and genotyped ((Formula presented.)) animals. The procedure ensures (Formula presented.) and (Formula presented.) are compatible so that both matrices refer to the same genetic base (?tuning?). Then (Formula presented.) is combined with a proportion of (Formula presented.) (?blending?) to avoid singularity problems and to account for the polygenic component not accounted for by markers. This computational procedure has been implemented in the reverse order (blending before tuning) following the sequential research developments. However, blending before tuning may result in less optimal tuning because the blended matrix already contains a proportion of (Formula presented.). In this study, the impact of ?tuning before blending? was compared with ?blending before tuning? on genomic estimated breeding values (GEBV), single nucleotide polymorphism (SNP) effects and indirect predictions (IP) from ssGBLUP using American Angus Association and Holstein Association USA, Inc. data. Two slightly different tuning methods were used; one that adjusts the mean diagonals and off-diagonals of (Formula presented.) to be similar to those in (Formula presented.) and another one that adjusts based on the average difference between all elements of (Formula presented.) and (Formula presented.). Over 6 million Angus growth rec... Presentar Todo |
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Palabras claves : |
Genetic base; Indirect predictions; Residual polygenic effect; Scaling of genomic matrices; Single-step genomic best linear unbiased prediction. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16748/1/J-Animal-Breeding-Genetics-2022-McWhorter-Implication-of-the-order-of-blending-and-tuning-when-computing-the-genomic.pdf
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/jbg.12734?download=true
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Marc : |
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022 $a0931-2668; eISSN: 1439-0388
024 7 $a10.1111/jbg.12734$2DOI
100 1 $aMCWHORTER, T.M.
245 $aImplication of the order of blending and tuning when computing the genomic relationship matrix in single-step GBLUP.$h[electronic resource]
260 $c2023
500 $aArticle history: Received 18 March 2019; Revised 15 July 2019; Accepted: 29 July 2019; First published 10 August 2022. Correspondence: McWhorter, T.M.; Department of Animal and Dairy Science, University of Georgia, Athens, GA, United States; email:taylor.mcwhorter@uga.edu -- This study was partially funded by Agriculture and Food Research Initiative Competitive Grant no. 2020?67015?31030 from the U.S. Department of Agriculture, Australian Government's National Institute of Food and Agriculture (Washington, DC). -- This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. License Creative Commons: https://creativecommons.org/licenses/by-nc-nd/4.0/
520 $aABSTRACT.- Single-step genomic BLUP (ssGBLUP) relies on the combination of the genomic ((Formula presented.)) and pedigree relationship matrices for all ((Formula presented.)) and genotyped ((Formula presented.)) animals. The procedure ensures (Formula presented.) and (Formula presented.) are compatible so that both matrices refer to the same genetic base (?tuning?). Then (Formula presented.) is combined with a proportion of (Formula presented.) (?blending?) to avoid singularity problems and to account for the polygenic component not accounted for by markers. This computational procedure has been implemented in the reverse order (blending before tuning) following the sequential research developments. However, blending before tuning may result in less optimal tuning because the blended matrix already contains a proportion of (Formula presented.). In this study, the impact of ?tuning before blending? was compared with ?blending before tuning? on genomic estimated breeding values (GEBV), single nucleotide polymorphism (SNP) effects and indirect predictions (IP) from ssGBLUP using American Angus Association and Holstein Association USA, Inc. data. Two slightly different tuning methods were used; one that adjusts the mean diagonals and off-diagonals of (Formula presented.) to be similar to those in (Formula presented.) and another one that adjusts based on the average difference between all elements of (Formula presented.) and (Formula presented.). Over 6 million Angus growth records and 5.9 million Holstein udder depth records were available. Genomic information was available on 51,478 Angus and 105,116 Holstein animals. Average realized relationship estimates among groups of animals were similar across scenarios. Scatterplots show that GEBV, SNP effects and IP did not noticeably change for all animals in the evaluation regardless of the order of computations and when using blending parameter of 0.05. Formulas were derived to determine the blending parameter that maximizes changes in the genomic relationship matrix and GEBV when changing the order of blending and tuning. Algebraically, the change is maximized when the blending parameter is equal to 0.5. Overall, tuning (Formula presented.) before blending, regardless of blending parameter used, had a negligible impact on genomic predictions and SNP effects in this study. © 2022 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd.
653 $aGenetic base
653 $aIndirect predictions
653 $aResidual polygenic effect
653 $aScaling of genomic matrices
653 $aSingle-step genomic best linear unbiased prediction
700 1 $aBERMANN, M.
700 1 $aGARCIA, A.L.S.
700 1 $aLEGARRA, A.
700 1 $aAGUILAR, I.
700 1 $aMISZTAL, I.
700 1 $aLOURENCO, D.
773 $tJournal of Animal Breeding and Genetics, 2023, volume 140, issue 1, pp. 60-78. OPEN ACCESS. doi: https://doi.org/10.1111/jbg.12734
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